A statistical comparison between music and G-music

Abstract : This paper adresses the statistical performance of subspace DoA estimation using a sensor array, in the asymptotic regime where the number of samples and sensors both converge to infinity at the same rate. Improved subspace DoA estimators were derived (termed as G-MUSIC) in previous works, and were shown to be consistent and asymptotically Gaussian distributed in the case where the number of sources and their DoA remain fixed. In this case, which models widely spaced DoA scenarios, it is established that the traditional MUSIC method also provides consistent DoA estimates having the same asymptotic MSE as the G-MUSIC estimates. In the case of closely spaced DoA (i.e. with a spacing of the order of a beamwidth), it is shown that G-MUSIC is still able to consistently separate the sources, while it is no longer the case for MUSIC.
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Communication dans un congrès
ICASSP, Apr 2015, Brisbane, Australia. pp.A, 2015, 〈10.1109/ICASSP.2015.7178487〉
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Dernière modification le : jeudi 5 juillet 2018 - 14:46:01
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P. Vallet, P Loubaton, X. Mestre. A statistical comparison between music and G-music. ICASSP, Apr 2015, Brisbane, Australia. pp.A, 2015, 〈10.1109/ICASSP.2015.7178487〉. 〈hal-01618519〉

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